As computers grow in both storage capacity and processing power, the collection of data has exploded. Unfortunately, as the amount and complexity of stored data grows, the ability to derive meaningful information from the stored data has been limited.
Data scientists have traditionally collected previously stored data and attempted to derive meaningful information through a query-based approach whereby a corpus of data is queried. Unfortunately, query-based approaches requires data scientists to guess at relationships in the stored data and then craft a meaningful query. Such an approach has limited value particularly as the amount and complexity of the data expands. Further, mistakes in formation of the query may lead to misleading results.